3D statistical facial reconstruction

The aim of craniofacial reconstruction is to produce a likeness of a face from the skull. Few works in computerized assisted facial reconstruction have been done in the past, due to poor machine performances and data availability, and major works are manually reconstructions. In this paper, we present an approach to build 3D statistical models of the skull and the face with soft tissues from the skull of one individual. Results on real data are presented and seem promising

Statistical skull models from 3D X-ray images

We present 2 statistical models of the skull and mandible built upon an elastic registration method of 3D meshes. The aim of this work is to relate degrees of freedom of skull anatomy, as static relations are of main interest for anthropology and legal medicine. Statistical models can effectively provide reconstructions together with statistical precision. In our applications, patient-specific meshes of the skull and the mandible are high-density meshes, extracted from 3D CT scans. All our patient-specific meshes are registrated in a subject-shared reference system using our 3D-to-3D elastic matching algorithm. Registration is based upon the minimization of a distance between the high density mesh and a shared low density mesh, defined on the vertexes, in a multi resolution approach. A Principal Component analysis is performed on the normalised registrated data to build a statistical linear model of the skull and mandible shape variation. The accuracy of the reconstruction is under the millimetre in the shape space (after rigid registration). Reconstruction errors for Scan data of tests individuals are below registration noise. To take in count the articulated aspect of the skull in our model, Kernel Principal Component Analysis is applied, extracting a non-linear parameter associated with mandible position, therefore building a statistical articulated 3D model of the skull.Comment: Proceedings of the Second International Conference on Reconstruction of Soft Facial Parts RSFP'200

Cognition, Affects et Interaction

International audienceCet ouvrage rassemble les travaux d’études et de recherche effectués dans le cadre du cours «Cognition, Affects et Interaction » que nous avons animé au 1er semestre 2015-2016. Cette deuxième édition de cours poursuit le principe inauguré en 2014 : aux cours magistraux donnés sur la thématique "Cognition, Interaction & Affects" qui donnent les outils méthodologiques des composantes de l’interaction socio-communicative, nous avons couplé une introduction à la robotique sociale et un apprentissage actif par travail de recherche en binômes. Le principe de ces travaux d’études et de recherche est d’effectuer une recherche bibliographique et de rédiger un article de synthèse sur un aspect de l’interaction homme-robot. Si plusieurs sujets ont été proposés aux étudiants en début d’année, certains binômes ont choisi d’aborder l’interaction avec un angle original qui reflète souvent les trajectoires de formation variés des étudiants en sciences cognitives (ingénierie, sociologie, psychologie, etc). Le résultat dépasse nos espérances : le lecteur trouvera une compilation d’articles argumentés de manière solide, rédigés de manière claire et présentés avec soin. Ces premières «publications» reflètent les capacités singulières de réflexion de cette promotion en nette augmentation par rapport à l’année précédente. Nous espérons que cette série d’ouvrages disponibles sous HAL puisse servir de point d’entrée à des étudiants ou chercheurs intéressés à explorer ce champ de recherches pluri-disciplinaire

Binding of the antibacterial drug clofoctol and analogues to the Cdc7/Dbf4 kinase complex. A computational study

Drugs targeting the cell division cycle kinase 7 (Cdc7) are actively searched for the treatment of different pathologies such as amyotrophic lateral sclerosis and cancer. Cdc7 interacts with multiple protein partners, including protein Dbf4 to form the Dbf4-dependent kinase (DDK) complex which regulates DNA replication initiation. Cdc7 and its activator Dbf4 are over-expressed in some cancers. The antibacterial drug clofoctol (CFT), used to treat respiratory tract infections, has been shown to block Cdc7 kinase activity, acting as a non-ATP-competitive inhibitor, capable of arresting DNA synthesis in cancer cells. We have modeled the interaction of CFT with the DDK complex and identified four potential binding sites at the interface of the Cdc7/Dbf4 heterodimer: at T109 and D128 (Cdc7), V220 and I330 (Dbf4). CFT behaves as an interfacial protein-protein inhibitor of the Cdc7/Dbf4 complex, limiting drug access to the proximal kinase site. Six CFT analogues have been tested for binding to the kinase complex. Two potent binders were analyzed in detail. The CFT structure was modulated to replace the two chlorine atoms with hydroxyl groups. The empirical potential energy of interaction (ΔE) calculated with hydroxylated compounds points to a more favorable interaction with the DDK complex, in particular at D128 site with the compound bearing two ortho-OH groups. Our work contributes to the identification of novel DDK inhibitors. DOI: http://dx.doi.org/10.5281/zenodo.552721

Assessing objective characterizations of phonetic convergence

International audienceThis paper focuses on the study of the convergence between characteristics of speech segments- i.e. spectral characteristics of speech sounds - during live interactions between speaking dyads. The interaction data has been collected using an original verbal game called 'verbal dominoes' that provides a dense sampling of the acoustic spaces of the interlocutors. Two methods for characterizing phonetic convergence are here compared. The first one is based on a fine-grained analysis of the spectra of central frames of vowels (LDA) while the second one uses a more global speaker recognition technique (LLR). We show that convergence rates calculated by the two techniques correlate as the number of dominoes increases and that the LDA method well resists to the decrease of training and test material. We finally comment the impact of several factors on the computed convergence rates, i.e. interlocutors' familiarity and sex pairs

Impact of Iris Size and Eyelids Coupling on the Estimation of the Gaze Direction of a Robotic Talking Head by Human Viewers

International audiencePrimates - and in particular humans-are very sensitive to the eye direction of congeners. Estimation of gaze of others is one of the basic skills for estimating goals, intentions and desires of social agents, whether they are humans or avatars. When building robots, one should not only supply them with gaze trackers but also check for the readability of their own gaze by human partners. We conducted experiments that demonstrate the strong impact of the iris size and the position of the eyelids of an iCub humanoid robot on gaze reading performance by human observers. We comment on the importance of assessing the robot's ability of displaying its intentions via clearly legible and readable gestures

Characterization of Audiovisual Dramatic Attitudes

International audienceIn this work we explore the capability of audiovisual parameters (such as voice frequency, rhythm, head motion or facial expressions) to discriminate among different dramatic attitudes. We extract the audiovisual parameters from an acted corpus of attitudes and structure them as frame, syllable, and sentence-level features. Using Linear Discriminant Analysis classifiers, we show that sentence-level features present a higher discriminating rate among the attitudes and are less dependent on the speaker than frame and sylable features. We also compare the classification results with the perceptual evaluation tests, showing that voice frequency is correlated to the perceptual results for all attitudes, while other features, such as head motion, contribute differently, depending both on the attitude and the speaker

Boucles de perception-action et interaction face-à-face

International audienceCet article explore un champ de recherches en plein essor : la communication face-à-face. Les performances et la robustesse des composants technologiques nécessaires à la mise en oeuvre de systèmes d'interaction face-à-face entre l'homme et un agent conversationnel - technologies vocales, vision par ordinateur, synthèse d'images, compréhension et génération de dialogues, etc. - sont maintenant matures. Nous esquissons ici un programme de recherche centré sur la modélisation des diverses boucles de perception-action impliquées dans la gestion de l'interaction et sur le paramétrage dynamique de ces boucles par les divers niveaux de compréhension de la scène dans laquelle humains, robots et agents conversationnels animés seront inévitablement plongés

Modeling Perception-Action Loops: Comparing Sequential Models with Frame-Based Classifiers

International audienceModeling multimodal perception-action loops in face-to-face interactions is a crucial step in the process of building sensory-motor behaviors for social robots or users-aware Embodied Conversational Agents (ECA). In this paper, we compare trainable behavioral models based on sequential models (HMMs) and classifiers (SVMs and Decision Trees) inherently inappropriate to model sequential aspects. These models aim at giving pertinent perception/action skills for robots in order to generate optimal actions given the perceived actions of others and joint goals. We applied these models to parallel speech and gaze data collected from interacting dyads. The challenge was to predict the gaze of one subject given the gaze of the interlocutor and the voice activity of both. We show that Incremental Discrete HMM (IDHMM) generally outperforms classifiers and that injecting input context in the modeling process significantly improves the performances of all algorithms